Download Putting Science into the Business of Data Science

What does business expect
from data science(tists)
The information herein is for informational purposes only and represents the opinions and views of Project
Botticelli and/or Rafal Lukawiecki. The material presented is not certain and may vary based on several factors.
Project Botticelli Ltd and Microsoft make no warranties, express, implied or statutory, as to the information in this
presentation.
Copyright © 2016 Project Botticelli Ltd unless noted otherwise. Some slides contain quotations from copyrighted
materials by other authors, as individually attributed or as already covered by Project Botticelli Ltd or Microsoft
Copyright ownerships. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or
may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for
informational purposes only and represents the current view of Project Botticelli Ltd as of the date of this
presentation. Because Project Botticelli & Microsoft must respond to changing market conditions, it should not be
interpreted to be a commitment on the part of Microsoft, and Microsoft and Project Botticelli cannot guarantee
the accuracy of any information provided after the date of this presentation. Project Botticelli makes no
warranties, express, implied or statutory, as to the information in this presentation. E&OE.
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Discover reason behind success, failure
Understand customers, products, patterns
Accurately plan future
Experiment before making decisions
Experiment with autonomous decision making (AI)
Advanced
analytics
Acquire
Explore,
visualise
Data
science
Copyright 2016 © Project Botticelli Ltd. All rights reserved.
Prepare
more than data engineering
Data
mining &
machine
learning
Big data
Statistics
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Data
science
Data wrangling
(munging), retrieval
+ storage
Algorithms that detect meaningful patterns in data
Copyright 2016 © Project Botticelli Ltd. All rights reserved.
Academic discipline
Part of IT and computing
Artificial Intelligence
Business
change
Machine
learning
models
Autonomous,
“intelligent”
decisions
Domain
expert
Data
expert
Data
scientist
Can we reduce
readmissions?
What is
readmission?
Does enough
data show
examples of
readmission?
Are the predictable
patterns of
readmitting?
Copyright 2016 © Project Botticelli Ltd. All rights reserved.
Start with a (business) goal
2. Express it as a testable hypothesis (H0 + HA, etc)
3. Progressively refine the hypothesis through
experiments and further models
1.
2.
3.
4.
5.
Define & initialise a model
Train model (process cases)
Validate model
Use it: Explore or Deploy
Update and revalidate
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1.
Experiments may be needed to get data
Copyright 2016 © Project Botticelli Ltd. All rights reserved.
State it as a series of hypotheses
control
Run
Evaluate
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Design
5-6%
http://papers.ssrn.com/sol3/Papers.cfm?abstract_id=1819486
Copyright 2016 © Project Botticelli Ltd. All rights reserved.
Data Driven Decision-making
Run on analytics
Copyright 2016 © Project Botticelli Ltd. All rights reserved.
Human intuition drives innovation
Advanced analytics validates facts
Data science enables Data Driven Decisions
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Copyright 2016 © Project Botticelli Ltd. All rights reserved.
Copyright © 2016 Project Botticelli Ltd unless noted otherwise.
Some slides contain quotations from copyrighted materials by other authors, as individually attributed or as already covered by Project Botticelli Ltd or Microsoft Copyright ownerships. All rights reserved. Microsoft, Windows, Windows Vista and other product names
are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Project Botticelli Ltd as of the date of this presentation. Because Project Botticelli
& Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft and Project Botticelli cannot guarantee the accuracy of any information provided after the date of this presentation.
Project Botticelli makes no warranties, express, implied or statutory, as to the information in this presentation. E&OE.